Using expert judgments to explore robust alternatives for forest management under climate change.

Area of Science:

• Environmental Management
• Decision Science
• Climate Change Adaptation

Background:

• Mountain pine beetle infestations, exacerbated by climate change, severely impact British Columbia's forests.
• Current forest management strategies may not adequately address future uncertainties.
• Existing decision-making approaches often require extensive data and analysis.

Purpose of the Study:

• To develop a practical, judgment-based approach for selecting robust forest management alternatives.
• To identify strategies that are reasonably likely to achieve objectives under a range of uncertainties.
• To inform decision-making for climate-exacerbated forest management challenges.

Main Methods:

• Developed a judgment-based framework using probability elicitation and judgmental forecasting.
• Used climate forecasts (10-90% cumulative distributions) to condition expert judgments.
• Elicited probabilistic performance data from 14 forest management specialists using a revised instrument.
• Applied stochastic dominance and sensitivity analysis to identify robust alternatives.

Main Results:

• Two flexible alternatives were consistently judged to perform better on average than current policies.
• Stochastic dominance analysis indicated a preference for adaptable management strategies.
• Sensitivity analysis explored judgment patterns and individual expert preferences.

Conclusions:

• Judgmental approaches to robust decision-making are valuable and warrant further investigation.
• Flexible forest management alternatives show promise for addressing climate change impacts.
• The developed approach offers a more practical alternative to data-intensive methods.